Partitioning Of Net Radiation Research Articles

Net radiation partitioning, evapotranspiration, and crop coefficients of the green dwarf coconut in Santa Izabel do Pará, Brazilian Amazon

Net radiation partitioning, evapotranspiration, and crop coefficients of the green dwarf coconut in Santa Izabel do Pará, Brazilian Amazon

Data‐Guided Exploration of the Energy Partitioning at Land Surface in the Contiguous US

AbstractThis study explores the climatic controls of the long‐term energy partitioning of net radiation into sensible heat and latent heat at watershed scale, by following a data‐guided approach. Collected data shows that the relationship between the evaporative fraction (ratio of latent heat to net radiation) and the aridity index (ratio of energy supply to water supply), which represents the climatic conditions at watershed scale, follows a trend similar to the Budyko curve. To explore the physical basis of this relationship, we hypothesize that there are mediating factors connecting energy partitioning with climate. Two potential mediating factors are considered, namely the equilibrium root zone soil moisture and land‐air temperature difference. We extract empirical relationships between the mediating factors and the partitioning fractions of water and energy fluxes based on observational data in 219 study watersheds across the contiguous US. With the obtained empirical relationships, we analytically derive two alternate Budyko‐type equations for energy partitioning, for each of the two mediating factors separately. Both equations show similar trends as the Budyko curve. We also derive a function to relate energy partitioning to water partitioning Budyko‐type equations, suggesting a close connection between the two. The study brings out the mediating roles of soil moisture and temperature gradient that connect water/energy partitioning with climate over long timescales in watersheds. In the process, the analysis results also provide useful insights about complex watershed system behavior. The observed relationships can be used to constrain hydrological and Earth system models and thus improve modeling performance.

Spatial heterogeneity effects on land surface modeling of water and energy partitioning

Abstract. Understanding the influence of land surface heterogeneity on surface water and energy fluxes is crucial for modeling earth system variability and change. This study investigates the effects of four dominant heterogeneity sources on land surface modeling, including atmospheric forcing (ATM), soil properties (SOIL), land use and land cover (LULC), and topography (TOPO). Our analysis focused on their impacts on the partitioning of precipitation (P) into evapotranspiration (ET) and runoff (R), partitioning of net radiation into sensible heat and latent heat, and corresponding water and energy fluxes. An initial set of 16 experiments were performed over the continental US (CONUS) using the E3SM land model (ELMv1) with different combinations of heterogeneous and homogeneous datasets. The Sobol' total and first-order sensitivity indices were utilized to quantify the relative importance of the four heterogeneity sources. Sobol' total sensitivity index measures the total heterogeneity effects induced by a given heterogeneity source, consisting of the contribution from its own heterogeneity (i.e., the first-order index) and its interactions with other heterogeneity sources. ATM and LULC are the most dominant heterogeneity sources in determining spatial variability of water and energy partitioning, mainly contributed by their own heterogeneity and slightly contributed by their interactions with other heterogeneity sources. Their heterogeneity effects are complementary, both spatially and temporally. The overall impacts of SOIL and TOPO are negligible, except TOPO dominates the spatial variability of R/P across the transitional climate zone between the arid western and humid eastern CONUS. Accounting for more heterogeneity sources improves the simulated spatial variability of water and energy fluxes when compared with ERA5-Land reanalysis dataset. An additional set of 13 experiments identified the most critical components within each heterogeneity source, which are precipitation, temperature, and longwave radiation for ATM, soil texture, and soil color for SOIL and maximum fractional saturated area parameter for TOPO.

NARR-based analysis of changes in the mesoscale wind and temperature over the Hudson Bay Lowlands and their impact on the surface energy balance: 1979–2018

The Hudson Bay exerts a strong advective influence on the surface energy balance of the adjacent Hudson Bay Lowlands (HBL) of Canada. The onshore winds are relatively cold and moist compared to the warmer and drier offshore winds. The contrasting thermal and humidity properties of these two air masses affect the partitioning of net radiation between the various heat fluxes over the HBL. We show that global warming has been accompanied by significant changes in the mesoscale wind regimes and the advective role of the Hudson Bay on the surface energy balance over the HBL. On average, we found a significant increasing trend in onshore wind frequency during the growing season of about 7% over the past 40 years. The most pronounced increase in onshore winds of 17% occurred in June during which ice cover on Hudson Bay has remained highly persistent over the past 40 years. The resulting shift from offshore to onshore winds dominance over the region has resulted in an enhancement of convective heat transfer to the atmosphere and a reduction of conductive heat transfer into the ground.

Enhanced Summertime Surface Warming Effects of Long‐Term Urbanization in a Humid Urban Agglomeration in China

AbstractIn this study, we examined the summertime climatic effects of urban expansion during 1990–2010 in the Yangtze River Delta (YRD) region by analyzing station observations and performing numerical simulations with the Weather Research and Forecast (WRF) model. Long‐term observations showed that urban area experienced a larger increase in summertime 2‐m air temperature than rural part during 1980–2018, and the influence of urbanization on the urban‐rural contrast was greater in the late stage (after 2000) than the early stage (before 2000). We applied the WRF model incorporated with historical land surface cover data (year 1990, 2000, and 2010) to further evaluate the climatic effects of long‐term urbanization. On average, urban expansion over 1990–2010 led to 0.75°C increase in daily average temperature (1.06°C in daily minimum and 0.45°C in daily maximum) during the summer. The summertime daily temperature range decreased by 0.61°C in urban environment during the same period. Compared to the warming effect of urbanization in the 1990s, both the magnitude and affected area have increased after the millennium. Also, urban expansion reduced moisture in low‐level atmosphere, and this urban dry island (UDI) effect was enhanced in the late stage. Less moisture in the atmosphere offset heat stress index induced by the warming temperature. We also found that the partitioning of net radiation between sensible and latent heat was the key factor that controlled urban warming effect.

Surface Energy Flux Estimation in Two Boreal Settings in Alaska Using a Thermal-Based Remote Sensing Model

Recent Arctic warming has led to changes in the hydrological cycle. Circum-Arctic and circumboreal ecosystems are showing evidence of “greening” and “browning” due to temperature warming leading to shrub encroachment, tree mortality and deciduousness. Increases in latent heat flux from increased evapotranspiration rates associated with deciduous-dominated ecosystems may be significant, because deciduous vegetation has extremely high-water use and water storage capacity compared to coniferous and herbaceous plant species. Thus, the impact of vegetation change in boreal ecosystems on regional surface energy balance is a significant knowledge gap that must be addressed to better understand observed trends in water use/availability and tree mortality. To this end, output from a two-source energy balance model (TSEB) with modifications for high latitude boreal ecosystems was evaluated using flux tower measurements and Terra/Aqua MODIS remote sensing data collected over the two largest boreal forest types in Alaska (birch and black spruce). Data under clear and overcast days and from leaf-out to senescence from 2012 to 2016 were used for validation. Using flux tower observations and local model inputs, modifications to the model formulation for soil heat flux, net radiation partitioning, and canopy transpiration were required for the boreal forest. These improvements resulted in a mean absolute percent difference of around 23% for turbulent daytime fluxes when surface temperature from the flux towers was used, similar to errors reported in other studies conducted in warmer climates. Results when surface temperature from Terra/Aqua MODIS estimates were used as model input suggested that these model improvements are pertinent for regional scale applications. Vegetation indices and LAI time-series from the Terra/Aqua MODIS products were confirmed to be appropriate for energy flux estimation in the boreal forest to describe vegetation properties (LAI and green fraction) when field observations are not available. Model improvements for boreal settings identified in this study will be implemented operationally over North America to map surface energy fluxes at regional scales using long time series of remote sensing estimates as part of NOAA’s GOES Evapotranspiration and Drought Information System.

Comparison of evapotranspiration and energy partitioning related to main biotic and abiotic controllers in vineyards using different irrigation methods

Knowledge of evapotranspiration (ET) and energy partitioning is useful for optimizing water management, especially in areas where water is scarce. A study was undertaken in a furrow-irrigated vineyard (2015) and a drip-irrigated vineyard (2017) in an arid region of north-west China to compare vineyard ET and energy partitioning and their responses to soil water content (SWC) and leaf area index (LAI). ET and soil evaporation (E) and transpiration (T) were determined using eddy covariance, microlysimeters, and sap flow. Seasonal average E/ET, T/ET, crop coefficient (Kc), evaporation coefficient (Ke), and basal crop coefficient (Kcb) were 0.50, 0.50, 0.67, 0.35, and 0.29, respectively, in the furrow-irrigated vineyard and 0.42, 0.58, 0.57, 0.29, and 0.43 in the drip-irrigated vineyard. The seasonal average partitioning of net radiation (Rn) into the latent heat flux (LE), sensible heat flux (H) and soil heat flux (G) (LE/Rn, H/Rn, and G/Rn), evaporative fraction (EF) and Bowen ratio (β) were 0.57, 0.26, 0.17, 0.69 and 0.63, respectively, in the furrow-irrigated vineyard and 0.46, 0.36, 0.17, 0.57 and 0.97 in the drip-irrigated vineyard. The LE/Rn, H/Rn, EF, and β were linearly correlated with LAI. The E, Kc, Ke, E/ET, LE/Rn, LEs/Rn (ratio of LE by soil E to Rn), H/Rn, EF and β were closely correlated with topsoil SWC (10 cm depth). Responses of ET and energy partitioning to the LAI and SWC differed under the two irrigation methods. Drip irrigation reduced seasonal average E/ET and increased average T/ET. From the perspective of energy partitioning, seasonal average H/Rn increased whereas LE/Rn, especially LEs/Rn, decreased. Compared with furrow irrigation, drip irrigation decreased the proportion of unproductive water consumption thereby contributing to enhanced water use efficiency and accumulation of dry matter.

Wind Sheltering Impacts on Land-Atmosphere Fluxes Over Fens

Wetlands and their ability to mitigate climate change motivates restorative and protective action; however, scientific understanding of land-atmosphere interactions is restricted by our limited continuous observations of gaseous fluxes. Many wetlands are small in spatial scale and embedded in forested landscapes. Yet, little is known about how the relative sheltering of forests affects net carbon (C) and energy balance. Here, we analyze coterminous USGS and Ameriflux eddy covariance flux tower observations over three years in two shrub fens in Northern Wisconsin, one more sheltered (US-ALQ) than the other (US-Los). Unsurprisingly, the open site showed higher overall wind speeds. This should have implications for atmospheric fluxes in wetlands as wind-forced processes are essential in promoting gas exchange over water. While both sites had similar half-hourly net ecosystem exchange of CO2 (NEE) during daytime, there were significant differences in nighttime NEE, as well as in net radiation partitioning in early spring and late summer. Sensible heat (H) fluxes were smaller at the sheltered fen except for the months of July-September. In contrast, latent heat (LE) fluxes were higher in every month except July. Additionally, sheltered fen ecosystem respiration had a weaker linear correlation with air temperature (R: 0.08 versus 0.57 for the open fen). Our work suggests that canopy sheltering does not cause significant differences in half-hourly NEE during the day, but rather the largest differences such as lower CO2 emissions occur at nighttime due to higher variance at very low wind speeds. Sheltering also influenced direction of air flow, mean wind speeds in day versus night, energy balance, and sensible and latent heat fluxes. We discuss implications of these findings for wetland restoration.

The Energy Side of Budyko: Surface‐Energy Partitioning From Hydrological Observations

AbstractLand‐surface partitioning of net radiation into sensible and latent heat fluxes is critical for hydroclimatic processes but remains highly uncertain due to limited observations. We show that a suitable extension of the Budyko's curve, a well‐known framework in hydrology for water balance estimation, can be utilized effectively to partition the surface energy fluxes by expressing the long‐term evaporative fraction (EF) as a function of the dryness index only. The combination of this energy partitioning method with hydrological observations allows us to estimate the surface energy components at watershed and continental scales. Using this new framework, we show that North American Regional Reanalysis data overestimate surface evaporation, likely influencing the modeling of atmospheric convection. The obtained hydrologic constrains on energy partitioning can be used to provide more accurate estimations of surface energy fluxes for hydroclimatic predictions.

A theoretical approach to assess soil moisture–climate coupling across CMIP5 and GLACE-CMIP5 experiments

Abstract. Terrestrial climate is influenced by various land–atmosphere interactions that involve numerous land surface state variables. In several regions on Earth, soil moisture plays an important role for climate via its control on the partitioning of net radiation into sensible and latent heat fluxes; consequently, soil moisture also impacts on temperature and precipitation. The Global Land–Atmosphere Coupling Experiment–Coupled Model Intercomparison Project phase 5 (GLACE-CMIP5) aims to quantify the impact of soil moisture on these important climate variables and to trace the individual coupling mechanisms. GLACE-CMIP5 provides experiments with different soil moisture prescriptions that can be used to isolate the effect of soil moisture on climate. Using a theoretical framework that relies on the distinct relation of soil moisture with evaporative fraction (the ratio of latent heat flux over net radiation) in different soil moisture regimes, the climate impact of the soil moisture prescriptions in the GLACE-CMIP5 experiments can be emulated and quantified. The framework-based estimation of the soil moisture effect on the evaporative fraction agrees very well with estimations obtained directly from the GLACE-CMIP5 experiments (pattern correlation of 0.85). Moreover, the soil moisture effect on the daily maximum temperature is well captured in regions where soil moisture exerts a strong control on latent heat fluxes. The theoretical approach is further applied to quantify the soil moisture contribution to the projected change of the temperature on the hottest day of the year, confirming recent estimations by other studies. Finally, GLACE-style soil moisture prescriptions are emulated in an extended set of CMIP5 models. The results indicate consistency between the soil moisture–climate coupling strength estimated with the GLACE-CMIP5 and the CMIP5 models. Although the theoretical approach is only designed to capture the local soil moisture–climate coupling strength, it can also help to distinguish non-local from local soil moisture–atmosphere feedbacks where sensitivity experiments (such as GLACE-CMIP5) are available. Overall, the theoretical framework-based approach presented here constitutes a simple and powerful tool to quantify local soil moisture–climate coupling in both the GLACE-CMIP5 and CMIP5 models that can be applied in the absence of dedicated sensitivity experiments.

Evaluating the Interplay Between Biophysical Processes and Leaf Area Changes in Land Surface Models.

Land Surface Models (LSMs) are essential to reproduce biophysical processes modulated by vegetation and to predict the future evolution of the land‐climate system. To assess the performance of an ensemble of LSMs (JSBACH, JULES, ORCHIDEE, CLM, and LPJ‐GUESS) a consistent set of land surface energy fluxes and leaf area index (LAI) has been generated. Relationships of interannual variations of modeled surface fluxes and LAI changes have been analyzed at global scale across climatological gradients and compared with those obtained from satellite‐based products. Model‐specific strengths and deficiencies were diagnosed for tree and grass biomes. Results show that the responses of grasses are generally well represented in models with respect to the observed interplay between turbulent fluxes and LAI, increasing the confidence on how the LAI‐dependent partition of net radiation into latent and sensible heat are simulated. On the contrary, modeled forest responses are characterized by systematic bias in the relation between the year‐to‐year variability in LAI and net radiation in cold and temperate climates, ultimately affecting the amount of absorbed radiation due to LAI‐related effects on surface albedo. In addition, for tree biomes, the relationships between LAI and turbulent fluxes appear to contradict the experimental evidences. The dominance of the transpiration‐driven over the observed albedo‐driven effects might suggest that LSMs have the incorrect balance of these two processes. Such mismatches shed light on the limitations of our current understanding and process representation of the vegetation control on the surface energy balance and help to identify critical areas for model improvement.

Modeling the contributions of global air temperature, synoptic-scale phenomena and soil moisture to near-surface static energy variability using artificial neural networks

Abstract. The static energy content of the atmosphere is increasing on a global scale, but exhibits important subglobal and subregional scales of variability and is a useful parameter for integrating the net effect of changes in the partitioning of energy at the surface and for improving understanding of the causes of so-called warming holes (i.e., locations with decreasing daily maximum air temperatures (T) or increasing trends of lower magnitude than the global mean). Further, measures of the static energy content (herein the equivalent potential temperature, θe) are more strongly linked to excess human mortality and morbidity than air temperature alone, and have great relevance in understanding causes of past heat-related excess mortality and making projections of possible future events that are likely to be associated with negative human health and economic consequences. New nonlinear statistical models for summertime daily maximum and minimum θe are developed and used to advance understanding of drivers of historical change and variability over the eastern USA. The predictor variables are an index of the daily global mean temperature, daily indices of the synoptic-scale meteorology derived from T and specific humidity (Q) at 850 and 500 hPa geopotential heights (Z), and spatiotemporally averaged soil moisture (SM). SM is particularly important in determining the magnitude of θe over regions that have previously been identified as exhibiting warming holes, confirming the key importance of SM in dictating the partitioning of net radiation into sensible and latent heat and dictating trends in near-surface T and θe. Consistent with our a priori expectations, models built using artificial neural networks (ANNs) out-perform linear models that do not permit interaction of the predictor variables (global T, synoptic-scale meteorological conditions and SM). This is particularly marked in regions with high variability in minimum and maximum θe, where more complex models built using ANN with multiple hidden layers are better able to capture the day-to-day variability in θe and the occurrence of extreme maximum θe. Over the entire domain, the ANN with three hidden layers exhibits high accuracy in predicting maximum θe > 347 K. The median hit rate for maximum θe > 347 K is > 0.60, while the median false alarm rate is ≈ 0.08.

Energy balance and evapotranspiration changes in a larch forest caused by severe disturbance during an early secondary succession

Larch, a deciduous needle-leaf gymnosperm, is widely distributed in cool temperate and boreal forests of the Northern Hemisphere. Thus, evaluating evapotranspiration (ET) in larch forests is important to elucidate energy and water cycles on a global scale. In addition, severe forest disturbance is expected to change ET and energy balance through a drastic change in the canopy structure. However, knowledge related to the environmental functions of larch forests in cool temperate regions remains lacking compared with Siberian larch forests. Furthermore, few reports describe quantified changes in ET and energy balance before and after forest disturbance. Therefore, for more than a decade, we measured sensible and latent heat fluxes using the eddy covariance technique above a larch forest in northern Japan and its succeeding ex-forest after a stand-replacing disturbance caused by windthrow. In general, the larch forest’s ET was not limited by water in contrast to that of a Siberian larch forest. Although the aboveground biomass decreased by 97% through the disturbance, both cumulative ET and latent heat flux normalized by incident solar radiation (lE/Rg) during the snow-free period of about seven months were decreased by only 24% in the second year after disturbance. The 24% decrease was caused by 17% decrease in the partition of incident solar radiation to net radiation (Rg/Rn) and 9% decrease in the partition of net radiation to ET (lE/Rn). The former resulted from increased albedo and decreased net longwave radiation, and the latter was mainly due to decrease in surface conductance. According to the vegetation recovery of shrubs and herbaceous plants, cumulative ET during the snow-free period increased gradually and almost reached pre-disturbance levels in six years. However, normalized ET by solar radiation (lE/Rg) decreased in the 11th and 12th years after reaching the pre-disturbance level. Positive relationship between cumulative ET and vegetation indices indicates that the ET recovery was due to vegetation recovery.

Evaluation of the Community Land Model simulated carbon and water fluxes against observations over ChinaFLUX sites

The Community Land Model (CLM) is an advanced process-based land surface model that simulates carbon, nitrogen, water vapor and energy exchanges between terrestrial ecosystems and the atmosphere at various spatial and temporal scales. We use observed carbon and water fluxes from five representative Chinese Terrestrial Ecosystem Flux Research Network (ChinaFLUX) eddy covariance tower sites to systematically evaluate the new version CLM4.5 and old version CLM4.0, and to generate insights that may inform future model developments. CLM4.5 underestimates the annual carbon sink at three forest sites and one alpine grassland site but overestimates the carbon sink of a semi-arid grassland site. The annual carbon sink underestimation for the deciduous-dominated forest site results from underestimated daytime carbon sequestration during summer and overestimated nighttime carbon emission during spring and autumn. Compared to CLM4.0, the bias of annual gross primary production (GPP) is reduced by 24% and 28% in CLM4.5 at two subtropical forest sites. However, CLM4.5 still presents a large positive bias in annual GPP. The improvement in net ecosystem exchange (NEE) is limited, although soil respiration bias decreases by 16%–43% at three forest sites. CLM4.5 simulates lower soil water content in the dry season than CLM4.0 at two grassland sites. Drier soils produce a significant drop in the leaf area index and in GPP and an increase in respiration for CLM4.5. The new fire parameterization approach in CLM4.5 causes excessive burning at the Changbaishan forest site, resulting in an unexpected underestimation of NEE, vegetation carbon, and soil organic carbon by 46%, 95%, and 87%, respectively. Overall, our study reveals significant improvements achieved by CLM4.5 compared to CLM4.0, and suggests further developments on the parameterization of seasonal GPP and respiration, which will require a more effective representation of seasonal water conditions and the partitioning of net radiation between sensible and heat fluxes.

Partitioning of net radiation and evapotranspiration over a superintensive drip-irrigated olive orchard

To evaluate the partitioning of net radiation (Rn) and actual evapotranspiration (ETa), measurements of Rn, sensible heat flux (H), soil heat flux (G), latent heat flux (LE), reference evapotranspiration (ETo), transpiration (Tp) and soil evaporation (Es) were taken during the 2009/2010 and 2010/2011 growing seasons on a flat and uniform olive (cv. Arbequina) orchard, located in the Pencahue Valley, Region del Maule, Chile (35°23′ LS; 71°44′ LW; 96 m above sea level). Olive trees were trained on a triangular hedgerow system with a plant density of 1333 trees ha−1 (superintensive). An eddy covariance system, sapflow sensors and microlysimeter were used to measure ETa, Tp and Es, respectively. Results indicated that the eddy covariance measurements showed a lack of the energy balance closure of 12.8 %. Values of LE, H and G were between 28–47, 34–68 and 2–6 % of Rn, respectively, while ratios of Tp and Es to ETa ranged between 0.64–0.74 and 0.26–0.36, respectively. During two growing seasons, the single crop coefficient (Kc = ETa/ETo) was between 0.27 and 0.66, while the dual crop coefficient (Tp/ETo + Es/ETo) ranged between 0.26 and 0.56. According to these results, H and Tp were the main component of Rn and ETa, respectively, for the particular conditions of the drip-irrigated olive orchard with a fractional cover of 30 % and wetted area of 4.5 %.

<b>Energy balance in the Cerrado of Ecological Station of Assis – Assis, São Paulo State, Brazil

This article presents the results of the net radiation partitioning (Rn) between latent heat (LE) and sensible heat fluxes (H) and its relationship with water availability (rain) in an area with Cerrado vegetation in the state Sao Paulo, Brazil. Heat fluxes follow the energy standard available in the environment, with higher values during the rainy season and lower values in the dry season. However, in the dry season, increased sensible heat flux over the latent heat flux was observed, which could be due to the lower water availability in the environment. Similar studies that have examined the dynamics of natural systems can contribute to the development of public policies for preservation and conservation of natural resources in a context in which the man-nature relationship is marked by imbalances in view of the form of use of natural resources based on predatory model adopted by society over the past 200 years.

Surface energy and radiation budget over a tropical station: An observational study

This study attempts to understand the variations in the radiation and surface energy budget parameters during days of occurrence and non occurrence of convective activity such as thunderstorms at Ranchi (23°25′N, 85°26′E), India using the special experimental data sets obtained during pre-monsoon month of May, 2008. For this purpose five continuous thunderstorm days (TD) of varying intensity, along with three non-thunderstorm days (NTD) preceding the TD are considered. Thunderstorms occurred at site are multi-cellular in nature. Change of wind direction and strong gusty winds are noticed in TD cases. Pre-dominant wind direction is south westerly for the TD; it is northwesterly during NTD. Sudden drop of air temperature and rise of relative humidity and rise/drop in atmospheric pressure is noticed during TD are found to be proportional to the intensity of thunderstorm event. More partitioning of net radiation (QN) is in to latent heat flux (QE) and the contribution of sensible heat flux (QH) and soil heat flux (QG) are same during TD. But in the NTD more partitioning of QN is in to QH followed by QG that of QE. Significant differences in radiation and energy budget components are noticed during TD and NTD events.

Coupling diffusion and maximum entropy models to estimate thermal inertia

Thermal inertia is a physical property of soil at the land surface related to water content. We developed a method for estimating soil thermal inertia using two daily measurements of surface temperature, to capture the diurnal range, and diurnal time series of net radiation and specific humidity. The method solves for soil thermal inertia assuming homogeneous 1-D diffusion of heat near the land surface. The solution uses a boundary condition taken as the maximum likelihood estimate of ground heat flux made by a probabilistic uncertainty model of the partitioning of net radiation based on the theory of maximum entropy production (MEP model). We showed that by coupling the 1-D diffusion and MEP models of energy transfer at the land surface, the number of free parameters in the MEP model can be reduced from two (P — soil thermal inertia and I — thermal inertia of convective heat transfer to the atmosphere) to one (P is defined by I). A sensitivity analysis suggested that, for the purpose of estimating thermal inertia, the coupled model should be parameterized by the ratio P/I. The coupled model was demonstrated at two semi-arid sites in the southwest United States to estimate thermal inertia and these thermal inertia values were used to estimate soil moisture. We found 1) parameterizing the MEP model with a constant annual P/I value resulted in surface flux estimates which were similar to those made when daily P and I parameters were derived directly from measurements of ground heat flux (Nash-Sutcliffe efficiency>0.95); 2) estimates of P made using the coupled model were superior to those made using the diffusion model with a common linear approximation of the ground heat flux boundary condition; and 3) thermal inertia was a better predictor of soil moisture in moderately wet conditions than in dry conditions due to a lack of sensitivity of thermal inertia to changes in soil moisture at low moisture contents.

Seasonality of water and carbon dioxide exchanges at a teak plantation in northern Thailand

The object of this study was to elucidate the seasonal patterns of energy partitioning of net radiation into sensible and latent heat fluxes and carbon dioxide (CO2) flux at a tropical deciduous forest site, i.e. a teak plantation in northern Thailand. In general, latent heat flux was more prominent than sensible heat flux in the wet (growing) season, whereas in the dry (dormant) season, sensible heat was the main form of energy emitted to the atmosphere. More specially, latent heat flux began to increase before leaf-out of teak trees and decreased 1 month earlier than leaf-fall initiation. Daytime net CO2 uptake appeared to increase with increasing amount of leaves but only at the beginning of the wet season; values peaked during the early part of wet season; and declined thereafter. This decline occurred about 3 months earlier than when latent heat flux began to decrease about 4 months earlier than the leaf-fall initiation. These results indicate that the seasonality of water and CO2 exchanges between the atmosphere and the tropical deciduous forest was substantially decoupled during the late wet season. This decoupling of the seasonality of water and carbon exchanges may be particularly important when modelling the ecohydrology of this tropical deciduous forest. Copyright © 2012 John Wiley & Sons, Ltd.

Energy exchange and evapotranspiration over two temperate semi-arid grasslands in North America

The seasonal and interannual variability in surface energy exchange and evapotranspiration (E) of two temperate semi-arid grasslands in southeastern Arizona, USA, were investigated using multi-year (2004–2007) eddy covariance measurements. The study sites, a post-fire site (AG) and an unburned site (KG), received 43–87% of the annual precipitation (P) during the North American Monsoon season (July–September), with the lowest values in the drought years of 2004 and 2005. Irrespective of the differences in temperature, surface albedo, vegetation cover and soil characteristics both sites responded similarly to changes in environmental conditions. The seasonal and interannual variations in the partitioning of net radiation to turbulent fluxes were mainly controlled by P through the changes in soil water content (θ) and vegetation growth. Drastic changes in albedo, vegetation growth and energy fluxes occurred following the onset of the monsoon season in July. During the dry or cool periods of autumn, winter and spring, the sensible heat flux was the largest component of the energy balance, whereas latent heat flux dominated during the warm and wet periods of summer. The dry-foliage Priestley–Taylor coefficient (α) declined when θ in the 0–15cm soil layer dropped below 0.08m3m−3 at AG, and 0.09m3m−3 at KG, respectively. The July–September average of dry-foliage surface conductance, α and E, reached their lowest values in 2004 at AG and in 2005 at KG. During July–September, monthly E was linearly correlated to the monthly mean θ and the broadband normalized difference vegetation index (NDVI), whereas during May–June the relationship between NDVI and E was not significant. Annual E varied from 264 to 322mm at AG and from 196 to 284mm at KG with the lowest value during the severe drought year at the site. July–September E had positive correlation with total P, the mean NDVI and the number of growing season days during that period. Annual P explained more than 80% of the variance in annual E.